214 related articles

MCP and Skills aren't alternatives — they occupy different layers of AI Agent architecture. This article breaks down Function Call, MCP, and Skills to clarify each layer's role.

Deep dive into the essential difference between Skill and MCP in AI Agent development. Skill handles the process layer for codifying workflows; MCP handles the capability layer for connecting external systems.

Understand the key differences between MCP (Model Context Protocol) and Skills through practical analogies and real testing scenarios to boost AI-driven test automation efficiency.

localskills.sh is a team-level AI skill and MCP server management platform that unifies distribution and reuse of AI Skills and Rules across Cursor, Claude Code, Windsurf, and more with a single install command.

localskills.sh is a team-level platform for managing AI Skills, Rules, and MCP servers across Cursor, Claude Code, and Windsurf with a single install command.

A detailed guide to Claude Code installation, domestic model switching, project analysis commands, and Git workflow practice to help developers quickly master this AI programming collaboration tool.

Deep dive into Agent skill routing: comparing pure model vs. pure retrieval approaches, with a detailed two-stage layered architecture balancing accuracy, latency, and cost.

Complete guide to Pi coding agent: design philosophy, installation, shortcuts, session management, and 7-layer customization architecture. How this 45K-star minimalist terminal tool redefines AI coding workflows.

Hands-on comparison of 7 Vibe Coding agents including Trae, Cursor, Claude Code, Codex, WorkBuddy & CoderWork, ranked by beginner-friendliness and performance.

Side-by-side review of 7 Vibe Coding agents including Trae, Cursor, Claude Code, Codex, WorkBuddy, and CoderWork, ranked by beginner-friendliness, performance, and ease of use.

Compare Codex and Claude Code AI agent programming tools. Learn AI Agent concepts, tool selection, cost analysis, and GPT account setup in this complete beginner's guide.

A deep dive into Agent Skills architecture: modular design, progressive disclosure mechanism, and how it differs from Multi-Agent systems for AI capability extension.

A detailed comparison of OpenAI Codex and Claude Code with hands-on testing. From AI agent concepts to account setup, helping developers quickly master AI coding agents.

A fresh grad interviewing for a GenAI Trainer role faced prime number coding and activation function questions while the interviewer used Gemini to generate questions live — exposing AI hiring chaos.

Understand Anything is a high-star open-source GitHub skill that runs static analysis on any codebase and generates interactive knowledge graphs. It supports Claude Code, Cursor, Copilot and other agents, letting engineers ask questions in natural language with path references.

Understand Anything is a high-star open-source GitHub skill that performs static analysis on any codebase to generate interactive knowledge graphs, supporting Claude Code, Cursor, Copilot and more.

Understand Anything is a high-star open-source GitHub skill that performs static analysis on any codebase to generate an interactive knowledge graph, supporting Claude Code, Cursor, Copilot and more.

A complete guide to Claude Code from beginner to enterprise practice: covering CLI installation, connecting domestic LLMs via CC Switch, basic commands, Git workflow integration, automated bug fixing, and engineering capabilities like MCP and SubAgents.

A step-by-step Pi Agent configuration tutorial covering installation, LLM connection, extension ecosystem, MCP setup, and Token-saving tips. Learn to build a truly controllable AI coding assistant.

A complete guide to the three core categories of AI tools in the testing era (personal assistants, CLI geek tools, AI IDEs), revealing the real challenges of AI test case generation and the new AI test development paradigm.